14 citations · 31 across the 8 of their papers we have counts for
6 papers · 1 filter
Unfolding Videos Dynamics via Taylor Expansion
Siyi Chen, Minkyu Choi, Zesen Zhao +3
Taking inspiration from physical motion, we present a new self-supervised dynamics learning strategy for videos: Video Time-Differentiation for Instance Discrimination (ViDiDi). Vi…
A Dual-Stream Neural Network Explains the Functional Segregation of Dorsal and Ventral Visual Pathways in Human Brains
Minkyu Choi, Kuan Han, Xiaokai Wang +2
The human visual system uses two parallel pathways for spatial processing and object recognition. In contrast, computer vision systems tend to use a single feedforward pathway, ren…
Human Eyes Inspired Recurrent Neural Networks are More Robust Against Adversarial Noises
Minkyu Choi, Yizhen Zhang, Kuan Han +2
Humans actively observe the visual surroundings by focusing on salient objects and ignoring trivial details. However, computer vision models based on convolutional neural networks…
Generating Goal-Directed Visuomotor Plans Based on Learning Using a Predictive Coding-type Deep Visuomotor Recurrent Neural Network Model
Minkyu Choi, Takazumi Matsumoto, Minju Jung +1
The current paper presents how a predictive coding type deep recurrent neural networks can generate vision-based goal-directed plans based on prior learning experience by examining…
Predictive Coding for Dynamic Visual Processing: Development of Functional Hierarchy in a Multiple Spatio-Temporal Scales RNN Model
Minkyu Choi, Jun Tani
The current paper proposes a novel predictive coding type neural network model, the predictive multiple spatio-temporal scales recurrent neural network (P-MSTRNN). The P-MSTRNN lea…
Predictive Coding for Dynamic Vision : Development of Functional Hierarchy in a Multiple Spatio-Temporal Scales RNN Model
Minkyu Choi, Jun Tani
The current paper presents a novel recurrent neural network model, the predictive multiple spatio-temporal scales RNN (P-MSTRNN), which can generate as well as recognize dynamic vi…